Truncateable predictive coding

ABSTRACT

A method, system, and computer program to encode and decode a channel coherence parameter applied on a frequency band basis, where the coherence parameters of each frequency band form a coherence vector. The coherence vector is encoded and decoded using a predictive scheme followed by a variable bit rate entropy coding.

TECHNICAL FIELD

Disclosed are embodiments related to predictive encoding and decodingrelated generally to audio signal processing.

BACKGROUND

Although the capacity in telecommunication networks is continuouslyincreasing, it is still of great interest to limit the requiredbandwidth per communication channel. Less transmission bandwidth foreach call allows the mobile network to service a larger number of usersin parallel. Additionally, lowering the transmission bandwidth yieldslower power consumption in both a mobile device and a base station ofthe mobile network. Such lower power consumption results in energy andcost saving for a mobile operator, while an end user may experienceprolonged battery life and increased talk-time.

One method for reducing transmission bandwidth in speech communicationis to utilize the natural pauses in speech. In most conversations, onlyone talker is active at a time and the natural pauses in speech by thetalker in one direction will typically occupy more than half of thesignal. A method of utilizing this property of a typical conversationfor the purpose of decreasing transmission bandwidth is to employ aDiscontinuous Transmission (DTX) scheme where active signal coding isdiscontinued during speech pauses. DTX schemes are standardized for all3GPP mobile telephony standards such as 2G, 3G and VoLTE. DTX schemesare also commonly used in Voice over IP systems.

When implementing a DTX scheme, it is common to transmit a very low bitrate encoding of the background noise to allow a Comfort Noise Generator(CNG) at the receiving end to fill speech pauses with a generatedbackground noise having similar characteristics to the originalbackground noise. The CNG makes the call sound more natural as thegenerated background noise is not switched on and off with the speechaccording to the DTX scheme. Complete silence during speech pauses isperceived as annoying to a listener and often leads to the misconceptionthat the call has been disconnected.

The DTX scheme further relies on a Voice Activity Detector (VAD) whichindicates to the system when to use active signal encoding methods orlow rate background noise encoding methods. The system may begeneralized to discriminate between other source types by using aGeneric Sound Activity Detector (GSAD also referred to as SAD), whichnot only discriminates speech from background noise, but also detectsmusic or other relevant signal types.

Communication services may be further enhanced by supporting stereo ormultichannel audio transmission. In such instances, a DTX and CNG systemmay need to consider the spatial characteristics of the audio signal inorder to provide a pleasant sounding comfort noise.

SUMMARY

Telecommunication traditionally utilizes a single channel for voicecommunication where a single microphone at each communication endpointis used to capture the sounds uttered by a speaker. Accordingly, thereis a need to enhance the communication experience by providing a moreprecise reconstruction of the spatial environment of the speaker. Suchenhancements may increase the intelligibility of the speech as it iseasier to separate a voice from the background noise if they areseparated in a spatial manner. Further, it is beneficial to havespeakers separated in an audio space for a teleconference scenario withmore than two participants.

A common comfort noise (CN) generation method used in 3GPP speech codecsis to transmit information to a receiver regarding the energy andspectral shape of the background noise for the speech pauses.Information regarding background noise can be transmitted using asignificantly less number of bits compared to regular coding of speechsegments.

At the receiver end, the CN is generated by creating a pseudo randomsignal and shaping the spectrum of the created signal with a filterbased on the received information regarding the background noise for thespeech pauses. Such signal generation and spectral shaping can be donein the time domain or the frequency domain.

Conventional methods of CN generation for a stereo DTX system use a monoencoder with a DTX system working separately on each channel. Forexample, a dual mono encoding is used for a dual channel stereo DTXsystem. Accordingly, the energy and spectral shape of the backgroundnoise transmitted to the receiver can be different for the left signaland the right signal. In most cases the difference in energy andspectral shape of the transmitted background noise between the leftsignal and the right signal may not be large, such differences mayresult in a significant difference in how “wide” the stereo image of thesignal is perceived by a listener. That is, if the pseudo random signalsused to generate the CN is synchronized between the left and the rightchannel the result will be a stereo signal which sounds very “narrow,”thereby giving the sensation of a sound originating from within the headof the listener. In contrast, if the pseudo random signals are notsynchronized, the very opposite sensation would be given to thelistener, i.e. a wide signal.

In most cases, an original background noise will have an energy andspectral shape, also referred to as a stereo image, that is in-betweenthese two extremes, i.e. the narrow signal and the wide signal. Thisresults in a detectable difference in the stereo image of the backgroundnoise when the system switches between active (speech) and non-active(noise) coding.

The stereo image of the original background noise may also change duringa call. For example, a user may be moving around and/or the environmentsurrounding the user may be changing. Conventional methods of CNgeneration, such as a dual mono encoding system, fail to provide anymechanisms to adapt to such changes.

Another disadvantage of using conventional methods of CN generation,such as dual mono encoding, is that the VAD decision will not besynchronized between the channels. This may lead to audible artifactswhen, for example, a left channel is encoded with active coding and aright channel is encoded with the low bit rate CN coding. The lack ofsynchronization of the VAD decision between the channels may cause thepseudo random signals used to generate the CN in the left and the rightchannel to be synchronized in some time instances and the unsynchronizedin others. As a result, the stereo image of the generated CN may togglebetween extremely wide and extremely narrow over time.

As shown above, there remains a need for an improved method of CNgeneration.

Accordingly, certain embodiments disclosed herein provide a method toencode a channel coherence parameter applied on a frequency band basis,where the coherence parameters of each band form a coherence vector. Thecoherence vector is encoded using a predictive scheme followed by avariable bit rate entropy coding. The coding scheme further improves theperformance through an adaptive inter-frame prediction.

For instance, in one aspect there is provided a method performed by anencoder to encode a vector. The method includes the encoder forming aprediction weighting factor. For each element of the vector, the encoderforms a first prediction of the vector element and a second predictionof the vector element. The encoder combines said first prediction andsaid second prediction using the prediction weighting factor into acombined prediction. The encoder forms a prediction residual using saidvector element and said combined prediction. The encoder encodes theprediction residual with a variable bit rate scheme. The encodertransmits the encoded prediction residual. In some embodiments, saidvector is one of a sequence of vectors. In some embodiments, the encoderreconstructs the vector based on the combined prediction and areconstructed prediction residual. In some embodiments, the encoderencodes and transmits the prediction weighting factor.

In some embodiments, the first prediction is an intra-frame predictionbased on the reconstructed vector elements. In such embodiments, theintra-frame prediction is formed by performing a process which includesselecting a predictor from a set of predictors, applying the selectedpredictor to the reconstructed vector elements; and encoding an indexcorresponding to the selected predictor.

In some embodiments, the second prediction is an inter-frame predictionbased on one or more vectors previously reconstructed for the sequenceof vectors. In such embodiments, the inter-frame prediction is formed byperforming a process which may include selecting a predictor from a setof predictors, applying the selected predictor to the one or morepreviously reconstructed vectors, and encoding an index corresponding tothe selected predictor. In some embodiments, a value from the previousreconstructed vector is used for the inter-frame prediction.

In some embodiments, the encoder quantizes the prediction residual toform a first residual quantizer index, wherein the first residualquantizer index is associated with a first code word.

In some embodiments, the step of encoding the prediction residual withthe variable bit rate scheme includes encoding the first residualquantizer index as a result of determining that the length of the firstcode word does not exceed the amount of remaining bits.

In some embodiments, the step of encoding the prediction residual withthe variable bit rate scheme includes obtaining a second residualquantizer index as a result of determining that the length of the firstcode word exceeds the amount of remaining bits, wherein the secondresidual quantizer index is associated with a second code word, andwherein the length of the second code word is shorter than the length ofthe first code word. In such embodiments, the encoder determines whetherthe length of the second code word exceeds the determined amount ofremaining bits.

In some embodiments, the encoder is further configured to receive afirst signal on a first input channel, receive a second signal on asecond input channel, determine spectral characteristics of the firstsignal and the second signal, determine a spatial coherence based on thedetermined spectral characteristics of the first signal and the secondsignal, and determine the vector based on the spatial coherence.

In some embodiments, the method is performed by the encoder in an audioencoder and decoder system comprising at least two input channels. Insome embodiments, the encoder is further configured to create a spectrumby performing a process comprising transforming the input channels andanalyzing the input channels in frequency bands. In some embodiments,the vector comprises a set of coherence values, and wherein each valuecorresponds to the coherence between two of the at least two inputchannels in a frequency band.

In another aspect there is provided a method performed by a decoder todecode a vector. The method includes the decoder obtaining a weightingfactor. For each element of the vector the decoder forms a firstprediction of the vector and a second prediction of the vector. Thedecoder combines said first prediction and said second prediction usingthe prediction weighting factor into a combined prediction. The decoderdecodes a received encoded prediction residual. The decoder reconstructsthe vector element based on the combined prediction and the decodedprediction residual. In some embodiments, said vector is one of asequence of vectors.

In some embodiments, the first prediction is an intra-frame predictionbased on the reconstructed vector elements. In such embodiments, theintra-frame prediction is formed by performing a process which includesreceiving and decoding a predictor and applying the decoded predictor tothe reconstructed vector elements.

In some embodiments, the second prediction is an inter-frame predictionbased on one or more vectors previously reconstructed for the sequenceof vectors. In such embodiments, the inter-frame prediction is formed byperforming a process which may include receiving and decoding apredictor; and applying the decoded predictor to the one or morepreviously reconstructed vectors. In some embodiments, a value fromprevious reconstructed vector is used for the inter-frame prediction.

In some embodiments, the step of decoding the encoded predictionresidual includes determining an amount of remaining bits available fordecoding and determining whether decoding the encoded predictionresidual exceeds the amount of remaining bits.

In some embodiments, the step of decoding the encoded predictionresidual includes setting the prediction residual as zero as a result ofdetermining that decoding the encoded prediction residual exceeds theamount of remaining bits.

In some embodiments, the step of decoding the encoded predictionresidual includes deriving the prediction residual based on a residualquantizer index as a result of determining that decoding the encodedprediction residual does not exceed the amount of remaining bits,wherein the residual quantizer index is a quantization of the predictionresidual.

In some embodiments, the step of obtaining the prediction weightingfactor comprises (i) deriving the prediction weighting factor or (ii)receiving and decoding the prediction weighting factor.

In some embodiments, the decoder generates signals for at least twooutput channels based on the reconstructed vector.

In yet another aspect there is provided an encoder comprising aprocessing circuitry. The processing circuitry is configured to causethe encoder to form a weighting factor, form a first prediction of avector element, form a second prediction of the vector element, and tocombine said first prediction and said second prediction using theprediction weighting factor into a combined prediction. The processingcircuitry is further configured to cause the encoder to form aprediction residual using said vector element and said combinedprediction, encode the prediction residual with a variable bit ratescheme and transmit the encoded prediction residual.

In yet another aspect there is provided a decoder comprising aprocessing circuitry. The processing circuitry being configured to causethe decoder to obtain a weighting factor, form a first prediction of avector element, form a second prediction of the vector element and tocombine said first prediction and said second prediction using theprediction weighting factor into a combined prediction. The processingcircuitry is further configured to cause the decoder to decode areceived encoded prediction residual and reconstruct the vector elementbased on the combined prediction and the decoded prediction residual.

The embodiments disclosed herein provide prediction and residual codingwhich offers rate scalability suitable for the variable bit budget. Theresidual coding may be truncated in relation to the predictive scheme.The adaptive inter-frame prediction finds a balance between theadvantages of inter-frame redundancy while minimizing the risk of errorpropagation in case of frame loss.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated herein and form partof the specification, illustrate various embodiments.

FIG. 1 illustrates a stereo encoding and decoding system according tosome embodiments.

FIG. 2 illustrates a stereo encoding and decoding system according tosome embodiments.

FIG. 3 is a flow chart illustrating an encoding process according tosome embodiments.

FIG. 4 illustrates a truncation scheme according to some embodiments.

FIG. 5 is a flow chart illustrating a decoding process according to someembodiments.

FIG. 6 is a flow chart illustrating a process according to oneembodiment.

FIG. 7 is a flow chart illustrating a process according to oneembodiment.

FIG. 8 is a block diagram of an encoder according to one embodiment.

FIG. 9 is a block diagram of a decoder according to one embodiment.

FIG. 10 is a diagram showing functional units of an encoder according toone embodiment.

FIG. 11 is a diagram showing functional units of a decoder according toone embodiment.

DETAILED DESCRIPTION

A method of achieving a spatial representation of a signal is to usemultiple microphones and to encode a stereo or multichannel signal. FIG.1 shows an illustration of a parametric stereo encoder 102 and decoder104. The encoder 102 performs an analysis of the input channel pair106A-106B and obtains a parametric representation of a stereo imagethrough parametric analysis 108 and reduces the channels a singlechannel through down-mix 110 thereby obtaining a down-mixed signal. Thedown-mixed signal is encoded with a mono encoding algorithm by a monoencoder 112 and the parametric representation of the stereo image isencoded by a parameter encoder 114. The encoded down-mixed signal andparametric representation of the stereo image is transmitted through abitstream 116. The decoder 104 employs a mono decoder 118 to apply amono decoding algorithm and obtains a synthesized down-mixed signal. Aparameter decoder 120 decodes the received parametric representation ofthe stereo image. The decoder 104 transforms the synthesized down-mixsignal into a synthesized channel pair through parametric synthesis 122using the decoded parametric representation of the stereo image.

FIG. 2 illustrates a parametric stereo encoding and decoding system 200according to some embodiments. As shown in FIG. 2, the parametric stereoencoding and decoding system 200 comprises a mono encoder 112 includinga CNG encoder 204 and a mono decoder 118 including a CNG decoder 206. Insome embodiments, the input signals 106A-106B comprise a channel pairdenoted as [l(m,n) r(m,n)], where l(m,n) and r(m,n) denote the inputsignals for the left and right channel, respectively, for sample index nof frame m. The signals are processed in frames of length N samples at asampling frequency F_(s), where the length of the frame may include anoverlap such as look-ahead and memory of past samples.

The parametric stereo encoding and decoding system 200 further comprisesa coherence analysis 202 in the parametric analysis 108 and a coherencesynthesis 208 in the parametric synthesis 122. The parametric analysis108 includes the capability to analyze the coherence of the inputsignals 106A-106B. The parametric analysis 108 may analyze the inputsignals 106A-106B when the mono encoder 112 is configured to operate asthe CNG encoder 204. In some embodiments, the input signals 106A-106Bmay be transformed to the frequency domain by means of, for example, aDFT or any other suitable filter-bank or transform such as QMF, hybridQMF, and MDCT. In some embodiments, a DFT or MDCT transform may be usedto transform the input signals 106A-106B to the frequency domain. Insuch embodiments, the input signals 106A-106B are typically windowedbefore the transformation. The choice of window depends on variousparameters, such as time and frequency resolution characteristics,algorithmic delay (overlap length), reconstruction properties, etc. Asan example, the DFT transformed channel pair denoted as [l(m,n) r(m,n)]is given by

${\left\lbrack {{L\left( {m,k} \right)}{R\left( {m,k} \right)}} \right\rbrack = \left\lbrack {DF{T\left( {l_{win}\left( {m,n} \right)} \right)}DF{T\left( {r_{win}\left( {m,n} \right)} \right)}} \right\rbrack},\left\{ \begin{matrix}{{n = 0},1,2,\ldots \mspace{14mu},\ {N - 1}} \\{{k = 0},1,2,\ldots \mspace{20mu},\ {N - 1}} \\{{{m = 0},1,2,\ldots}\ }\end{matrix} \right.$

A general definition of the channel coherence C_(gen)(f) for frequency fis given by

${{C_{gen}(f)} = \frac{{{S_{ϰy}(f)}}^{2}}{{S_{ϰϰ}(f)}{S_{yy}(f)}}},$

where S_(xx)(f) and S_(yy)(f) represent the power spectra of the twochannels 106A-106B and S_(xy)(f) is the cross power spectrum. In theexemplary DFT based solution, the channel coherence spectra may berepresented by the DFT spectra given by

${C\left( {k,m} \right)} = \frac{\left| {{L\left( {m,k} \right)}{R\left( {m,k} \right)}^{*}} \right|^{2}}{\left| {L\left( {m,k} \right)} \middle| {}_{2} \middle| {R\left( {m,k} \right)} \right|^{2}}$

where * denotes the complex conjugate. To reduce the number of bitsrequired to encode the coherence values, the spectrum is divided intosub frequency bands (also referred to as coherence bands). In someembodiments, the bandwidth of the sub frequency bands is configured tomatch the perceived frequency resolution with narrow bandwidth for thelow frequencies and increasing bandwidth for higher frequencies. It isto be noted that terms channel coherence and spatial coherence are usedinterchangeably throughout the description.

Accordingly, the analysis of the coherence provides a value per subfrequency band, thereby forming a vector of coherence values,C_(m)=[C_(1,m) C_(2,m) . . . C_(b,m) . . . C_(N) _(bnd,m) ], whereN_(bnd) is the number of coherence bands, b is the band index, and m isthe frame index. The coherence values C_(b,m) are then encoded to bestored or transmitted to a decoder. In some embodiments, the powerspectra may be averaged over time or low-pass filtered to form morestable estimates of the power spectrum. Further details regarding thecoherence analysis is described in International Application PublicationNo. WO 2015/122809.

When decoding a CNG frame, the decoder 104 produces two CNG framescorresponding to the two synthesis channels 210A-210B. In someembodiments, the two CNG frames are generated to have a minimumcoherence/correlation. Such CNG frames with minimumcoherence/correlation may be generated by operating the CNG decoder 206two separate times with the same parameters, but using two differentpseudo-random number generators according to some embodiments. In someembodiments, the two CNG frames with minimum coherence/correlation maybe generated by applying a decorrelator function which modifies the finestructure of the CNG frame while maintaining a minimum impact on themagnitude spectrum. The target coherence is then obtained by combiningthe two generated CNG signals using a method described in InternationalApplication Publication No. WO 2015/122809.

The proposed solution disclosed herein applies to a stereo encoder anddecoder architecture or a multi-channel encoder and decoder where thechannel coherence is considered in channel pairs. Referring back to FIG.2, the mono encoder 112 may comprise a stereo encoder VAD according tosome embodiments. The stereo encoder VAD may indicate to the CNG encoder204 that a signal contains background noise, thereby activating the CNGencoder 204. Accordingly, a CNG analysis comprising the coherenceanalysis 202 is activated in the parametric analysis 108 and the monoencoder 112 initiates the CNG encoder 204. As a result, an encodedrepresentation of the coherence and the mono CNG is bundled together inthe bitstream 116 for transmission and/or storing. The decoder 104identifies the stereo CNG frame in the bitstream 116, decodes the monoCNG and the coherence values, and synthesizes the target coherence asdescribed, for instance, in International Application Publication No. WO2015/122809.

The disclosed embodiments described herein relate to the encoding anddecoding of the coherence values for the CNG frames.

The encoding of the coherence vector described herein considers thefollowing properties: (1) adaptable encoding to a varying per-frame bitbudget B_(m), (2) the coherence vector shows strong frame-to-framesimilarity, and (3) error propagation should be kept low for lostframes.

To address the varying per-frame bit budget, a coarse-fine encodingstrategy is implemented. More specifically, the coarse encoding is firstachieved at a low bit rate and the subsequent fine encoding may betruncated when the bit limit is reached.

In some embodiments, the coarse encoding is performed utilizing apredictive scheme. In such embodiments, a predictor works along thecoherence vector for increasing bands b and estimates each coherencevalue based on the previous values of the vector. That is, anintra-frame prediction of the coherence vector is performed and is givenby:

$C_{{intra},b,m}^{(q)} = \left\{ \begin{matrix}{0,\ {b = 1}} \\{{\sum_{i = 1}^{b - 1}{p_{b,i}^{(q)}C_{i,m,}2}} \leq b \leq N_{bnd}}\end{matrix} \right.$

Each predictor set P(q) consists of (N_(bnd)−1) predictors, eachpredictor comprising (b 1) predictor coefficients for each band b whereq=1, 2, . . . N_(q) and N_(q) indicates a total number of predictorsets. As shown above, there are no previous values when b=1 and theintra-frame prediction of the coherence is zero. As an example, apredictor set number q when there are six coherence bands, N_(bnd)=6, isgiven by

P^((q)) = {[p_(2, 1)^((q))], [p_(3, 1)^((q))p_(3, 2)^((q))], [p_(4, 1)^((q))p_(4, 2)^((q))p_(4, 3)^((q))],   [p_(5, 1)^((q))p_(5, 2)^((q))p_(5, 3)^((q))p_(5, 4)^((q))], [p_(6, 1)^((q))p_(6, 2)^((q))p_(6, 3)^((q))p_(6, 4)^((q))p_(6, 5)^((q))]}.

As another example, the total number of predictor sets may be four, i.e.N_(q)=4, which indicates that the selected predictor set may be signaledusing 2 bits. In some embodiments, predictor coefficients for apredictor set q may be addressed sequentially and stored in a singlevector of length Σ_(i) ^(N) ^(bnd) ⁻¹i=N_(bnd)(N_(bnd)−1)/2.

FIG. 3 is a flow chart illustrating an encoding process 301 according tosome embodiments. The encoding process 301 may be performed by theencoder 102 according to the following steps:

In step 300, for each frame m, a bit variable (also referred to as a bitcounter) to keep track of the bits spent for the encoding is initializedto zero (B_(curr,m)=0). The encoding algorithm receives a coherencevector (C_(b,m)) to encode, a copy of the previous reconstructedcoherence vector (Ĉ_(b,m-1)), and a bit budget B_(m). In someembodiments, the bits spent in preceding encoding steps may be includedin B_(m) and B_(curr,m). In such embodiments, the bit budget in thealgorithm below can be given by B_(m)−B_(curr,m).

In step 310, a predictor set P^((q*)) which gives the smallestprediction error out of the available predictors P^((q)), q=1, 2, . . ., N_(q) is selected. The selected predictor set is given by

${q^{*} = {\underset{q^{\prime}}{argmin}\; {\sum_{b = 2}^{N_{bnd}}{{C_{{intra},b,m}^{(q^{\prime})} - C_{b,m}}}^{2}}}},{q^{\prime} = 1},2,\ldots \mspace{14mu},{N_{q}.}$

In some embodiments, b=1 is omitted from the predictor set because theprediction is zero and contribution to the error will be the same forall predictor sets. The selected predictor set index is stored and thebit counter (B_(curr,m)) is increased with the required number of bits,e.g. B_(curr,m):=B_(curr,m)+2 if two bits are required to encode thepredictor set.

In step 320, a prediction weighting factor α is computed. The predictionweighting factor is used to create a weighted prediction as described instep 360 below. The prediction weighting factor needs to be available inthe decoder 104. In some embodiments, the prediction weighting factor αis encoded and transmitted to the decoder 104. In such embodiments, thebit counter (B_(curr,m)) is increased by the amount of bits required forencoding the prediction weighting factor. In other embodiments, thedecoder may derive the prediction weight factor based on otherparameters already available in the decoder 104.

For each of the bands b=1, 2, . . . N_(bnd) in step 330, the followingsteps are performed:

In step 340, an intra-frame prediction value, Ĉ_(intra,b,m) ^((q)), isobtained. There are no preceding encoded coherence values for the firstband (b=1). In some embodiments, the intra-frame prediction for thefirst band may be set to zero, Ĉ_(intra,1,m) ^((q))=0. In someembodiments, the intra-frame prediction for the first band may be set toan average value C, Ĉ_(intra,1,m) ^((q))=C.

In some alternative embodiments, the coherence value of the first bandmay be encoded separately. In such embodiments, the first value isencoded using a scalar quantizer to produce reconstructed valueĈ_(SQ,1,m). Accordingly, the intra-frame prediction for the first bandmay be set to the reconstructed value, Ĉ_(intra,1,m) ^((q))=Ĉ_(SQ,1,m).The bit counter, B_(curr,m), is increased by the amount of bits requiredto encode the coherence value of the first band. For example, if 3 bitsare used to encode the coherence value of the first band, 3 bits areadded to the current amount of bits spent for the encoding, for example,B_(curr,m):=B_(curr,m)+3.

For the remaining bands b=2, 3, . . . , N_(bnd), the intra-frameprediction Ĉ_(pred,b,m) ^((q)) is based on previously encoded coherencevalues, i.e. Ĉ_(intra,b,m) ^((q))=Σ_(i=1) ^(b-1)p_(b,i) ^((q))Ĉ_(i,m).

In step 350, an inter-frame prediction value, Ĉ_(inter,b,m), is obtainedbased on previously reconstructed coherence vector elements from one ormore preceding frames. In cases where the background noise is stable orchanging slowly, the frame-to-frame variation in the coherence bandvalues C_(b,m) will be small. Hence, an inter-frame prediction using thevalues from previous frame will often be a good approximation whichyields a small prediction residual and a small residual coding bit rate.As an example, a last reconstructed value for band b may be used for aninter-frame prediction value, i.e. Ĉ_(inter,b,m)=Ĉ_(b,m-1). Aninter-frame linear predictor considering two or more preceding framescan be formulated as Ĉ_(inter,m)=Σ_(n=1) ^(N) ^(inter) g_(n)Ĉ_(m-n),where Ĉ_(inter,m) denotes the column vector of inter-frame predictedcoherence values for all bands b of frame m, Ĉ_(m-n) represents thereconstructed coherence values for all bands b of frame m−n and g_(n) isthe linear predictor coefficients which span N_(inter) preceding frames.g_(n) may be selected out of a pre-defined set of predictors, in whichcase the used predictor needs to be represented with an index that maybe communicated to a decoder.

In step 360, a weighted prediction, Ĉ_(pred,b,m) ^((q)), is formed basedon the intra-frame prediction, Ĉ_(intra,b,m) ^((q)), the inter-frameprediction, Ĉ_(inter,b,m) ^((q)), and the prediction weighting factor α.In some embodiments, the weighted prediction is given Ĉ_(pred,b,m)^((q))=αĈ_(intra,b,m) ^((q))+(1−α)Ĉ_(inter,b,m).

In step 370, a prediction residual is computed and encoded. In someembodiments, the prediction residual is computed based on the coherencevector and the weighted prediction, i.e. r_(b,m)=C_(b,m)−Ĉ_(pred,b,m)^((q)). In some embodiments, a scalar quantizer is used to quantize theprediction residual to an index I_(b,m). In such embodiments, the indexis given by I_(b,m)=SQ(r_(b,m)) where SQ(x) is a scalar quantizerfunction with a suitable range. An example of a scalar quantizer isshown in Table 1 below. Table 1 shows an example of reconstructionlevels and quantizer indices for a prediction residual.

TABLE 1 I = SQ(x) 0 1 2 3 4 5 6 7 8 Reconstruction −0.4 −0.3 −0.2 −0.1 00.1 0.2 0.3 0.4 levels

In some embodiments, the index I_(b,m) is encoded with a variable lengthcodeword scheme that consumes fewer bits for smaller values. Someexamples for encoding the prediction residual are Huffman coding,Golomb-Rice coding, and unary coding (the unary coding is the same asthe Golomb-Rice coding with divisor 1). In the step of encoding theprediction residual, the remaining bit budget (B_(m)−B_(curr,m)) needsto be considered. If the length of the codeword L_(code) (I_(b,m))corresponding to index I_(b,m) fits within the remaining bit budget,i.e. L_(code)(I_(b,m))≤B_(m)−B_(curr,m), the index I_(b,m) is selectedas the final index I_(b,m)*. If the remaining bits are not sufficient toencode the index I_(b,m), a bit rate truncation strategy is applied. Insome embodiments, the bit rate truncation strategy includes encoding thelargest possible residual value, assuming that smaller residual valuescost fewer bits. Such a rate truncation strategy can be achieved byreordering a codebook as illustrated by table 400 in FIG. 4. FIG. 4shows an exemplary quantizer table 400 with unary codeword mapping forthe scalar quantizer example shown in Table 1. In some embodiments, abit rate truncation may be achieved by advancing upwards in the table400 in steps of two until codeword 0 is reached. That is, FIG. 4illustrates a truncation scheme of moving upwards from a long code wordto a shorter code word. To maintain the correct sign of thereconstructed value, each truncation steps takes two steps up the table400, as indicated by the dashed and solid arrows for negative andpositive values respectively. By moving upward in the table 400 in stepsof two, a new truncated codebook index I_(b,m) ^(trunc) can be found.The upward search continues until L_(code)(I_(b,m)^(trunc))≤B_(m)−B_(curr,m) is satisfied or the top of the table 400 hasbeen reached.

If the length of the codeword determined by the upward search fits doesnot exceed bit budget, the final index is selected I_(b,m)*=I_(b,m)^(trunc) and I_(b,m)* is output to the bitstream and the reconstructedresidual is formed based on the final index, i.e. {circumflex over(r)}_(b,m)=R(I_(b,m)*).

If after the upward search, the length of the codeword still exceeds thebit budget, L_(cede)(I_(b,m) ^(trunc))>B_(m)−B_(curr,m), this means thatthe bit limit has been reached B_(m)=B_(curr,m). In such instances, thereconstructed residual is set to zero {circumflex over (r)}_(b,m)=0 andan index is not added to the bitstream. Since the decoder keeps asynchronized bit counter, B_(curr,m), the decoder may detect thissituation and use {circumflex over (r)}_(b,m)=0 without explicitsignaling.

In an alternative embodiment, if the length of the codeword associatedwith the initial index exceeds the bit budget, the residual value isimmediately set to zero, thereby foregoing the upward search describeabove. This could be beneficial if computational complexity is critical.

In step 380, a reconstructed coherence value Ĉ_(b,m) is formed based onthe reconstructed prediction residual and the weighted prediction, i.e.Ĉ_(b,m)=Ĉ_(pred,b,m) ^((q))+{circumflex over (r)}_(b,m).

In step 390, the bit counter is incremented accordingly. As describedabove, the bit counter is increased throughout the encoding process 301.

In some embodiments, the frame-to-frame variations in the coherencevector are small. Hence, the inter-frame prediction using the previousframe value is often a good approximation which yields a smallprediction residual and a small residual coding bit rate. Additionally,the prediction weighting factor α serves the purpose of balancing thebit rate versus the frame loss resilience.

FIG. 5 is a flow chart illustrating a decoding process 501 according tosome embodiments. The decoding process 501 corresponding to the encodingprocess 301 may be performed by the decoder 104 according to thefollowing steps:

In step 500, a bit counter, B_(curr,m), configured to keep track of thebits spent during the decoding process 501 is initialized to zero, i.e.B_(curr,m)=0. For each frame m, the decoder 104 obtains a copy of thelast reconstructed coherence vector Ĉ_(b,m-1) and a bit budget B_(m).

In step 510, a selected predictor set P^((q*)) is decoded from thebitstream 116. The bit counter is increased by the amount of bitsrequired to decode the selected predictor set. For example, if two bitsare required to decode the selected predictor set, the bit counter,B_(curr,m,) is increased by two, i.e. B_(curr,m):=B_(curr,m)+2.

In step 520, the prediction weighting factor α corresponding to theweighting factor used in the encoder 102 is derived.

For each of the bands b=1, 2, . . . N_(bnd) in step 530, the followingsteps are performed:

In step 540, an intra-prediction value, Ĉ_(intra,b,m) ^((q)), isobtained. The intra-frame prediction for the first band is obtainedsimilarly to step 340 of the encoding process 301. Accordingly, theintra-frame prediction for the first frame may be set to zero(Ĉ_(intra,1,m) ^((q))=0), an average value C (Ĉ_(intra,1,m) ^((q))=C) ora coherence value of the first band may be decoded from the bitstream116 and the intra-frame prediction for the first frame may be set toreconstructed value Ĉ_(SQ,1,m) (Ĉ_(intra,1,m) ^((q))=Ĉ_(SQ,1,m)). If thecoherence value of the first band is decoded, the bit counter,B_(curr,m), is increased by the amount of bits required for thedecoding. For example, if three bits are required for decoding thecoherence value of the first band, the bit counter, B_(curr,m), isincreased by three, i.e. B_(curr,m):=B_(curr,m)+3.

For the remaining bands b=2, 3, . . . , N_(bnd), the intra-frameprediction Ĉ_(pred,b,m) ^((q)) is based on the previously decodedcoherence values, i.e. Ĉ_(intra,b,m) ^((q))=Σ_(i=1) ^(b-1)p_(b,i)^((q))Ĉ_(i,m).

In step 550, an inter-frame prediction value, Ĉ_(inter,b,m), is obtainedsimilarly to step 350 of the encoding process 301. As an example, a lastreconstructed value for band b may be used for an inter-frame predictionvalue, i.e. Ĉ_(inter,b,m)=Ĉ_(b,m-1).

In step 560, a weighted prediction, Ĉ_(pred,b,m) ^((q)), is formed basedon the intra-frame prediction, Ĉ_(intra,b,m) ^((q)), the inter-frameprediction, Ĉ_(inter,b,m), and the prediction weighting factor α. Insome embodiments, the weighted prediction is given by Ĉ_(pred,b,m)^((q))=αĈ_(intra,b,m) ^((q))+(1−α)Ĉ_(inter,b,m).

In step 570, a reconstructed prediction residual, {circumflex over(r)}_(b,m), is decoded. If the bit counter, B_(curr,m), is below the bitlimit, i.e. B_(curr,m)<B_(m), the reconstructed prediction residual isderived from an available quantizer index {circumflex over(r)}_(b,m)=R(I_(b,m)*). If the bit counter equals or exceeds the bitlimit, the reconstructed prediction residual is set to zero, i.e.{circumflex over (r)}_(b,m)=0.

In step 580, a coherence value Ĉ_(b,m) is reconstructed based on thereconstructed prediction residual and the weighted prediction, i.e.Ĉ_(b,m)=Ĉ_(pred,b,m) ^((q))+{circumflex over (r)}_(b,m). In step 590,the bit counter is incremented.

In some embodiments, further enhancements of the CNG may be required inthe encoder. In such embodiments, a local decoder will be run in theencoder where the reconstructed coherence values Ĉ_(b,m) are used.

FIG. 6 is a flow chart illustrating a process 600, according to someembodiments, that is performed by an encoder 102 to encode a vector.Process 600 may begin with step 602 in which the encoder forms aprediction weighting factor. The following steps 604 through 614 may berepeated for each element of the vector. In step 606, the encoder formsa first prediction of the vector element. In step 604, the encoder formsa second prediction of the vector element. In step 608, the encodercombines said first prediction and said second prediction using theprediction weighting factor into a combined prediction. In step 610, theencoder forms a prediction residual using said vector element and saidcombined prediction. In step 612, the encoder encodes the predictionresidual with a variable bit rate scheme. In step 614, the encoderreconstructs the vector element based on the combined prediction and areconstructed prediction residual. In step 616, the encoder transmitsthe encoded prediction residual. In some embodiments, the encoderencodes also the prediction weighting factor and transmits the encodedprediction weighting factor.

In some embodiments, the first prediction is an intra-frame predictionbased on the reconstructed vector elements. In such embodiments, theintra-frame prediction is formed by performing a process which includesselecting a predictor from a set of predictors, applying the selectedpredictor to the reconstructed vector elements; and encoding an indexcorresponding to the selected predictor.

In some embodiments, the second prediction is an inter-frame predictionbased on one or more vectors previously reconstructed for the sequenceof vectors. In such embodiments, the inter-frame prediction is formed byperforming a process which may include selecting a predictor from a setof predictors, applying the selected predictor to the one or morepreviously reconstructed vectors, and encoding an index corresponding tothe selected predictor. In embodiments, where the inter-frame predictionis based on only one previously reconstructed vector, a value from theprevious reconstructed vector may be used for the inter-frameprediction, i.e., for frequency band b, a last reconstructed value (i.e.vector element) for band b may be used for an inter-frame predictionvalue.

In some embodiments, the process 600 includes a further step in whichthe prediction residual is quantized to form a first residual quantizerindex, wherein the first residual quantizer index is associated with afirst code word.

In some embodiments, the step of encoding the prediction residual withthe variable bit rate scheme includes encoding the first residualquantizer index as a result of determining that the length of the firstcode word does not exceed the amount of remaining bits.

In some embodiments, the step of encoding the prediction residual withthe variable bit rate scheme includes obtaining a second residualquantizer index as a result of determining that the length of the firstcode word exceeds the amount of remaining bits, wherein the secondresidual quantizer index is associated with a second code word, andwherein the length of the second code word is shorter than the length ofthe first code word. In such embodiments, the process 600 includes afurther step in which the encoder determines whether the length of thesecond code word exceeds the determined amount of remaining bits.

In some embodiments, the process 600 includes a further step in whichthe encoder receives a first signal on a first input channel, receives asecond signal on a second input channel, determines spectralcharacteristics of the first signal and the second signal, determines aspatial coherence based on the determined spectral characteristics ofthe first signal and the second signal, and determines the vector basedon the spatial coherence.

In some embodiments, the process 600 is performed by the encoder in anaudio encoder and decoder system comprising at least two input channels.In some embodiments, the process 600 includes a further step in whichthe encoder creates a spectrum by performing a process comprisingtransforming the input channels and analyzing the input channels infrequency bands. In some embodiments, the vector comprises a set ofcoherence values, and wherein each value corresponds to the coherencebetween two of the at least two input channels in a frequency band.

FIG. 7 is a flow chart illustrating a process 700, according to someembodiments, that is performed by a decoder 104 to decode a vector.Process 700 may begin with step 702 in which the decoder obtains aprediction weighting factor. The following steps 704 through 712 may berepeated for each element of the vector. In step 704, the decoder formsa first prediction of the vector element. In step 706, the decoder formsa second prediction of the vector element. In step 708, the decodercombines said first prediction and said second prediction using theprediction weighting factor into a combined prediction. In step 710, thedecoder decodes a received encoded prediction residual. In step 712, thedecoder reconstructs the vector element based on the combined predictionand the prediction residual. In some embodiments, said vector is one ofa sequence of vectors.

In some embodiments, the first prediction is an intra-frame predictionbased on the reconstructed vector elements. In such embodiments, theintra-frame prediction is formed by performing a process which includesreceiving and decoding a predictor and applying the decoded predictor tothe reconstructed vector elements.

In some embodiments, the second prediction is an inter-frame predictionbased on one or more vectors previously reconstructed for the sequenceof vectors. In such embodiments, the inter-frame prediction is formed byperforming a process which may include receiving and decoding apredictor; and applying the decoded predictor to the one or morepreviously reconstructed vectors. In embodiments, where the inter-frameprediction is based on only one previously reconstructed vector, a valuefrom the previous reconstructed vector may be used for the inter-frameprediction, i.e., for frequency band b, a last reconstructed value (i.e.vector element) for band b may be used for an inter-frame predictionvalue.

In some embodiments, the step of decoding the encoded predictionresidual includes determining an amount of remaining bits available fordecoding and determining whether decoding the encoded predictionresidual exceeds the amount of remaining bits.

In some embodiments, the step of decoding the encoded predictionresidual includes setting the prediction residual as zero as a result ofdetermining that decoding the encoded prediction residual exceeds theamount of remaining bits.

In some embodiments, the step of decoding the encoded predictionresidual includes deriving the prediction residual based on a residualquantizer index as a result of determining that decoding the encodedprediction residual does not exceed the amount of remaining bits,wherein the residual quantizer index is a quantization of the predictionresidual.

In some embodiments, the step of obtaining the prediction weightingfactor comprises (i) deriving the prediction weighting factor or (ii)receiving and decoding the prediction weighting factor.

In some embodiments, the process 700 further includes a step in whichthe decoder generates signals for at least two output channels based onthe reconstructed vector.

FIG. 8 is a block diagram of encoder 102 according to some embodiments.As shown in FIG. 8, encoder 102 may comprise: a processing circuit (PC)802, which may include one or more processors (P) 855 (e.g., a generalpurpose microprocessor and/or one or more other processors, such as anapplication specific integrated circuit (ASIC), field-programmable gatearrays (FPGAs), and the like); a network interface 848 comprising atransmitter (Tx) 845 and a receiver (Rx) 847 for enabling encoder 102 totransmit data to and receive data from other nodes connected to anetwork 110 (e.g., an Internet Protocol (IP) network) to which networkinterface 848 is connected; circuitry 803 (e.g., radio transceivercircuitry comprising an Rx 805 and a Tx 806) coupled to an antennasystem 804 for wireless communication with UEs); and local storage unit(a.k.a., “data storage system”) 808, which may include one or morenon-volatile storage devices and/or one or more volatile storage devices(e.g., random access memory (RAM)). In embodiments where PC 802 includesa programmable processor, a computer program product (CPP) 841 may beprovided. CPP 841 includes a computer readable medium (CRM) 842 storinga computer program (CP) 843 comprising computer readable instructions(CRI) 844. CRM 842 may be a non-transitory computer readable medium,such as, but not limited, to magnetic media (e.g., a hard disk), opticalmedia, memory devices (e.g., random access memory, flash memory), andthe like. In some embodiments, the CRI 844 of computer program 843 isconfigured such that when executed by data processing apparatus 802, theCRI causes encoder 102 to perform steps described herein (e.g., stepsdescribed herein with reference to the flow charts and/or message flowdiagrams). In other embodiments, encoder 102 may be configured toperform steps described herein without the need for code. That is, forexample, PC 802 may consist merely of one or more ASICs. Hence, thefeatures of the embodiments described herein may be implemented inhardware and/or software.

In an embodiment an encoder 102 comprises a processing circuitry 802,the processing circuitry being configured to cause the encoder to form aprediction weighting factor, and for each element of the vector: form afirst prediction of a vector element, form a second prediction of thevector element, form a prediction weighting factor, and to combine saidfirst prediction and said second prediction using the predictionweighting factor into a combined prediction. The processing circuitry isfurther configured to cause the encoder to form a prediction residualusing said vector element and said combined prediction, encode theprediction residual with a variable bit rate scheme and transmit theencoded prediction residual.

FIG. 9 is a block diagram of decoder 104 according to some embodiments.As shown in FIG. 9, decoder 104 may comprise: a processing circuit (PC)902, which may include one or more processors (P) 955 (e.g., a generalpurpose microprocessor and/or one or more other processors, such as anapplication specific integrated circuit (ASIC), field-programmable gatearrays (FPGAs), and the like); a network interface 948 comprising atransmitter (Tx) 945 and a receiver (Rx) 947 for enabling decoder 104 totransmit data to and receive data from other nodes connected to anetwork 110 (e.g., an Internet Protocol (IP) network) to which networkinterface 948 is connected; circuitry 903 (e.g., radio transceivercircuitry comprising an Rx 905 and a Tx 906) coupled to an antennasystem 904 for wireless communication with UEs); and local storage unit(a.k.a., “data storage system”) 908, which may include one or morenon-volatile storage devices and/or one or more volatile storage devices(e.g., random access memory (RAM)). In embodiments where PC 902 includesa programmable processor, a computer program product (CPP) 941 may beprovided. CPP 941 includes a computer readable medium (CRM) 942 storinga computer program (CP) 943 comprising computer readable instructions(CRI) 944. CRM 942 may be a non-transitory computer readable medium,such as, but not limited, to magnetic media (e.g., a hard disk), opticalmedia, memory devices (e.g., random access memory, flash memory), andthe like. In some embodiments, the CRI 944 of computer program 943 isconfigured such that when executed by data processing apparatus 902, theCRI causes decoder 104 to perform steps described herein (e.g., stepsdescribed herein with reference to the flow charts and/or message flowdiagrams). In other embodiments, decoder 104 may be configured toperform steps described herein without the need for code. That is, forexample, PC 902 may consist merely of one or more ASICs. Hence, thefeatures of the embodiments described herein may be implemented inhardware and/or software.

In an embodiment a decoder 104 comprises a processing circuitry 902, theprocessing circuitry being configured to cause the decoder to obtain aweighting factor, and for each element of the vector: form a firstprediction of a vector element, form a second prediction of the vectorelement, obtain a prediction weighting factor and to combine said firstprediction and said second prediction using the prediction weightingfactor into a combined prediction. The processing circuitry is furtherconfigured to cause the decoder to decode a received encoded predictionresidual and reconstruct the vector element based on the combinedprediction and the decoded prediction residual.

FIG. 10 is a diagram showing functional units of encoder 102 accordingto some embodiments. As shown in FIG. 10, encoder 102 includes a firstforming unit 1002 for forming a first prediction of the vector element;a second forming unit 1004 for forming a second prediction of the vectorelement; a third forming unit 1006 and an encoding unit 1008 for formingand encoding a prediction weighting factor; a combining unit 1010 forcombining said first prediction and said second prediction using theprediction weighting factor into a combined prediction; a fourth formingunit 1012 for forming a prediction residual using said vector elementand said combined prediction; an encoding unit 1014 for encoding theprediction residual with a variable bit rate scheme; and a transmittingunit 1016 for transmitting the encoded prediction weighting factor andthe encoded prediction residual.

FIG. 11 is a diagram showing functional units of decoder 104 accordingto some embodiments. As shown in FIG. 11, decoder 104 includes a firstforming unit 1102 for forming a first prediction of the vector element;a second forming unit 1104 for forming a second prediction of the vectorelement; an obtaining unit 1106 for obtaining a prediction weightingfactor; a combining unit 1108 for combining said first prediction andsaid second prediction using the prediction weighting factor into acombined prediction; a receiving unit 1110 and a decoding unit 1112 forreceiving and decoding an encoded prediction residual; and areconstructing unit 1114 for reconstructing the vector element based onthe combined prediction and the prediction residual.

Here now follows a set of example embodiments to further describe theconcepts presented herein.

A1. A method for encoding a vector, the method comprising:

forming a first prediction of the vector;

forming a second prediction of the vector;

forming and encoding a prediction weighting factor;

combining said first prediction and said second prediction using theprediction weighting factor into a combined prediction;

forming a prediction residual using said vector and said combinedprediction;

encoding the prediction residual with a variable bit rate scheme; and

transmitting the encoded prediction weighting factor and the encodedprediction residual.

A2. The method of embodiment A1, wherein said vector is one of asequence of vectors.

A3. The method of embodiment A2, further comprising:

reconstructing the vector based on the combined prediction and areconstructed prediction residual.

A4. The method of embodiment A3, wherein the first prediction is anintra-frame prediction based on the reconstructed vector.

A5. The method of embodiment A2 or A4, wherein the second prediction isan inter-frame prediction based on one or more vectors previouslyreconstructed for the sequence of vectors.

A6. The method in embodiment A4, wherein the intra-frame prediction isformed by performing a process comprising:

selecting a predictor from a set of predictors;

applying the selected predictor to the reconstructed vector; and

encoding an index corresponding to the selected predictor.

A7. The method in embodiment A5, wherein the inter-frame prediction isformed by performing a process comprising:

selecting a predictor from a set of predictors;

applying the selected predictor to the one or more previouslyreconstructed vectors;

and encoding an index corresponding to the selected predictor.

A8. The method of any one of embodiments A1-A7, further comprising:

quantizing the prediction residual to form a first residual quantizerindex, wherein the first residual quantizer index is associated with afirst code word.

A9. The method of embodiment A8, wherein encoding the predictionresidual with the variable bit rate scheme comprises:

determining an amount of remaining bits available for the encoding; and

determining whether the length of the first code word exceeds the amountof remaining bits.

A10. The method of embodiment A9, wherein encoding the predictionresidual with the variable bit rate scheme comprises:

as a result of determining that the length of the first code word doesnot exceed the amount of remaining bits, encoding the first residualquantizer index.

A11. The method of embodiment A9, wherein encoding the predictionresidual with the variable bit rate scheme comprises:

as a result of determining that the length of the first code wordexceeds the amount of remaining bits, obtaining a second residualquantizer index, wherein the second residual quantizer index isassociated with a second code word, and wherein the length of the secondcode word is shorter than the length of the first code word; and

determining whether the length of the second code word exceeds thedetermined amount of remaining bits.

A12. The method of any one of embodiments A1-A11, further comprising:

receiving a first signal on a first input channel;

receiving a second signal on a second input channel;

determining spectral characteristics of the first signal and the secondsignal; determining a spatial coherence based on the determined spectralcharacteristics of the first signal and the second signal; and

determining the vector based on the spatial coherence.

A13. The method of any one of embodiments A1-A11, wherein the method isperformed in an audio encoder and decoder system comprising at least twoinput channels.

A14. The method of embodiment A13, the method further comprising:

creating a spectrum by performing a process comprising transforming theinput channels and analyzing the input channels in frequency bands.

A15. The method of embodiment A14, wherein the vector comprises a set ofcoherence values, and wherein each value corresponds to the coherencebetween two of the at least two input channels in a frequency band.

B1. A method for decoding a vector, the method comprising:

forming a first prediction of the vector;

forming a second prediction of the vector;

obtaining a prediction weighting factor;

combining said first prediction and said second prediction using theprediction weighting factor into a combined prediction;

receiving and decoding an encoded prediction residual; and

reconstructing the vector based on the combined prediction and theprediction residual.

B2. The method of embodiment B1, wherein said vector is one of asequence of vectors.

B3. The method of embodiment B1 or B2, wherein the first prediction isan intra-frame prediction based on the reconstructed vector.

B4. The method of embodiment B2 or B3, wherein the second prediction isan inter-frame prediction based on one or more vectors previouslyreconstructed for the sequence of vectors.

B5. The method of embodiment B3, wherein the intra-frame prediction isformed by performing a process comprising:

receiving and decoding a predictor; and

applying the decoded predictor to the reconstructed vector.

B6. The method of embodiment B4, wherein the inter-frame prediction isformed by performing a process comprising:

receiving and decoding a predictor; and

applying the decoded predictor to the one or more previouslyreconstructed vectors.

B7. The method of any one of embodiments B1-B6, wherein decoding theencoded prediction residual further comprises:

determining an amount of remaining bits available for decoding; and

determining whether decoding the encoded prediction residual exceeds theamount of remaining bits.

B8. The method of embodiment B7, wherein decoding the encoded predictionresidual further comprises:

as a result of determining that decoding the encoded prediction residualexceeds the amount of remaining bits, setting the prediction residual aszero.

B9. The method of embodiment B7, wherein decoding the encoded predictionresidual further comprises:

as a result of determining that decoding the encoded prediction residualdoes not exceed the amount of remaining bits, deriving the predictionresidual based on a residual quantizer index, wherein the residualquantizer index is a quantization of the prediction residual.

B10. The method of any one of embodiments B1-B9, wherein the step ofobtaining the prediction weighting factor comprises one of (i) derivingthe prediction weighting factor and (ii) receiving and decoding theprediction weighting factor.

B11. The method of any one of embodiments B1-B10, further comprising:

generating signals for at least two output channels based on thereconstructed vector.

Also, while various embodiments of the present disclosure are describedherein, it should be understood that they have been presented by way ofexample only, and not limitation. Thus, the breadth and scope of thepresent disclosure should not be limited by any of the above-describedexemplary embodiments. Moreover, any combination of the above-describedelements in all possible variations thereof is encompassed by thedisclosure unless otherwise indicated herein or otherwise clearlycontradicted by context.

Additionally, while the processes described above and illustrated in thedrawings are shown as a sequence of steps, this was done solely for thesake of illustration. Accordingly, it is contemplated that some stepsmay be added, some steps may be omitted, the order of the steps may bere-arranged, and some steps may be performed in parallel.

1. A method for encoding a vector, the method comprising: forming aprediction weighting factor; for each element of the vector: forming afirst prediction of the vector element; forming a second prediction ofthe vector element; combining said first prediction and said secondprediction using the prediction weighting factor into a combinedprediction; forming a prediction residual using said vector element andsaid combined prediction; and encoding the prediction residual with avariable bit rate scheme; and transmitting the encoded predictionresidual.
 2. The method of claim 1, wherein said vector is one of asequence of vectors.
 3. The method of claim 1, further comprising:reconstructing the vector element based on the combined prediction and areconstructed prediction residual.
 4. The method of claim 3, wherein thefirst prediction is an intra-frame prediction based on the reconstructedvector elements.
 5. The method of claim 2, wherein the second predictionis an inter-frame prediction based on one or more vectors previouslyreconstructed for the sequence of vectors.
 6. The method of claim 4,wherein the intra-frame prediction is formed by performing a processcomprising: selecting a predictor from a set of predictors; applying theselected predictor to the reconstructed vector elements; and encoding anindex corresponding to the selected predictor.
 7. The method of claim 5,wherein a value from the previous reconstructed vector is used for theinter-frame prediction.
 8. The method of claim 5, wherein theinter-frame prediction is formed by performing a process comprising:selecting a predictor from a set of predictors; applying the selectedpredictor to the one or more previously reconstructed vectors; andencoding an index corresponding to the selected predictor.
 9. The methodof claim 1, further comprising: quantizing the prediction residual toform a first residual quantizer index, wherein the first residualquantizer index is associated with a first code word.
 10. The method ofclaim 9, wherein encoding the prediction residual with the variable bitrate scheme comprises: determining an amount of remaining bits availablefor the encoding; and determining whether the length of the first codeword exceeds the amount of remaining bits.
 11. The method of claim 10,wherein encoding the prediction residual with the variable bit ratescheme comprises: as a result of determining that the length of thefirst code word does not exceed the amount of remaining bits, encodingthe first residual quantizer index.
 12. The method of claim 10, whereinencoding the prediction residual with the variable bit rate schemecomprises: as a result of determining that the length of the first codeword exceeds the amount of remaining bits, obtaining a second residualquantizer index, wherein the second residual quantizer index isassociated with a second code word, and wherein the length of the secondcode word is shorter than the length of the first code word; anddetermining whether the length of the second code word exceeds thedetermined amount of remaining bits.
 13. The method of claim 1, furthercomprising: encoding the prediction weighting factor; and transmittingthe encoded prediction weighting factor.
 14. (canceled)
 15. (canceled)16. (canceled)
 17. (canceled)
 18. A method for decoding a vector, themethod comprising: obtaining a prediction weighting factor; and for eachelement of the vector: forming a first prediction of the vector element;forming a second prediction of the vector element; combining said firstprediction and said second prediction using the prediction weightingfactor into a combined prediction; decoding a received encodedprediction residual; and reconstructing the vector element based on thecombined prediction and the decoded prediction residual.
 19. The methodof claim 18, wherein said vector is one of a sequence of vectors. 20.The method of claim 18, wherein the first prediction is an intra-frameprediction based on the reconstructed vector elements.
 21. The method ofclaim 19, wherein the second prediction is an inter-frame predictionbased on one or more vectors previously reconstructed for the sequenceof vectors.
 22. The method of claim 20, wherein the intra-frameprediction is formed by performing a process comprising: receiving anddecoding a predictor; and applying the decoded predictor to thereconstructed vector elements.
 23. The method of claim 21, wherein avalue from previous reconstructed vector is used for the inter-frameprediction.
 24. The method of claim 21, wherein the inter-frameprediction is formed by performing a process comprising: receiving anddecoding a predictor; and applying the decoded predictor to the one ormore previously reconstructed vectors.
 25. The method of claim 18,wherein decoding the encoded prediction residual further comprises:determining an amount of remaining bits available for decoding; anddetermining whether decoding the encoded prediction residual exceeds theamount of remaining bits.
 26. The method of claim 25, wherein decodingthe encoded prediction residual further comprises: as a result ofdetermining that decoding the encoded prediction residual exceeds theamount of remaining bits, setting the prediction residual as zero. 27.The method of claim 25, wherein decoding the encoded prediction residualfurther comprises: as a result of determining that decoding the encodedprediction residual does not exceed the amount of remaining bits,deriving the prediction residual based on a residual quantizer index,wherein the residual quantizer index is a quantization of the predictionresidual.
 28. The method of claim 18, wherein the step of obtaining theprediction weighting factor comprises one of (i) deriving the predictionweighting factor and (ii) receiving and decoding the predictionweighting factor.
 29. (canceled)
 30. (canceled)
 31. An encodercomprising a processing circuitry, the processing circuitry beingconfigured to cause the encoder to: form a prediction weighting factor;for each element of a vector: form a first prediction of a vectorelement; form a second prediction of the vector element; combine saidfirst prediction and said second prediction using the predictionweighting factor into a combined prediction; form a prediction residualusing said vector element and said combined prediction; and encode theprediction residual with a variable bit rate scheme; and transmit theencoded prediction residual.
 32. (canceled)
 33. A decoder comprising aprocessing circuitry, the processing circuitry being configured to causethe decoder to: obtain a prediction weighting factor; and for eachelement of a vector: form a first prediction of a vector element; form asecond prediction of the vector element; combine said first predictionand said second prediction using the prediction weighting factor into acombined prediction; decode a received encoded prediction residual; andreconstruct the vector element based on the combined prediction and thedecoded prediction residual.
 34. (canceled)
 35. (canceled)